1 citations · 1 across the 2 of their papers we have counts for
4 papers
Global-Supervised Contrastive Loss and View-Aware-Based Post-Processing for Vehicle Re-Identification
Zhijun Hu, Yong Xu, Jie Wen +4
In this paper, we propose a Global-Supervised Contrastive loss and a view-aware-based post-processing (VABPP) method for the field of vehicle re-identification. The traditional sup…
Vehicle Re-identification Based on Dual Distance Center Loss
Zhijun Hu, Yong Xu, Jie Wen +2
Recently, deep learning has been widely used in the field of vehicle re-identification. When training a deep model, softmax loss is usually used as a supervision tool. However, the…
Dedge-AGMNet:an effective stereo matching network optimized by depth edge auxiliary task
Weida Yang, Xindong Ai, Zuliu Yang +2
To improve the performance in ill-posed regions, this paper proposes an atrous granular multi-scale network based on depth edge subnetwork(Dedge-AGMNet). According to a general fac…
Incomplete Multi-view Clustering via Graph Regularized Matrix Factorization
Jie Wen, Zheng Zhang, Yong Xu +1
Clustering with incomplete views is a challenge in multi-view clustering. In this paper, we provide a novel and simple method to address this issue. Specifically, the proposed meth…